XTTS v2
XTTS v2 (Cross-lingual Text-to-Speech v2) is a multilingual voice cloning and text-to-speech model developed by Coqui AI that can replicate any person's voice from just a 6-second audio sample and synthesize speech in 17 supported languages. Built on a GPT-like autoregressive architecture paired with a HiFi-GAN vocoder, XTTS v2 with 467 million parameters produces natural-sounding speech with realistic prosody, intonation, and emotional expressiveness. The model's cross-lingual capability allows a voice cloned from an English sample to speak fluently in French, Spanish, German, Turkish, and other supported languages while maintaining the original speaker's vocal characteristics. XTTS v2 achieves this through a language-agnostic speaker embedding space that separates voice identity from linguistic content. The synthesis quality approaches human-level naturalness for many languages, with particularly strong performance in English, Spanish, and Portuguese. The model supports streaming inference for real-time applications, generating speech with latencies suitable for conversational AI and interactive voice assistants. Released under the MPL-2.0 license, XTTS v2 is open source and can be deployed locally for privacy-sensitive applications. Common use cases include creating multilingual audiobook narrations, localizing video content with consistent voice identity, building accessible text-to-speech interfaces, developing custom voice assistants, podcast production, and e-learning content creation. The model provides a Python API and can be fine-tuned on additional voice data for improved quality with specific speakers or specialized domains.
Key Highlights
Speech Synthesis in 17 Languages
Capability to produce high-quality speech synthesis with natural intonation and stress in 17 languages including Turkish.
Voice Cloning in 6 Seconds
Enables personalized speech generation by cloning the target voice with just a 6-second audio sample.
Real-Time Streaming Support
Provides suitable output for live applications and chatbots with real-time audio streaming at low latency.
Emotion Control
Ability to control different emotional tones such as happiness, sadness, and excitement in generated speech.
About
XTTS v2 (Cross-lingual Text-to-Speech v2) is a multilingual voice cloning and text-to-speech model developed by Coqui AI, representing a significant advancement in cross-lingual speech synthesis technology. With just a short audio sample of up to 6 seconds, it can clone any person's voice and use that voice across 17 different languages with remarkable fidelity and naturalness. It produces natural and fluent speech synthesis in many languages including Turkish, making it an indispensable tool for global content production, localization projects, and multilingual communication platforms.
The most important feature of XTTS v2 is its zero-shot voice cloning capability that requires no model retraining. The user provides a short audio recording from the target speaker, and the model analyzes this audio to capture the speaker's tone, emphasis, speaking rhythm, and unique vocal characteristics. As a result, it voices new texts in that person's distinctive voice with convincing authenticity across all supported languages. This feature offers revolutionary convenience for podcast production, audiobook creation, and content generation at scale. The model's hybrid architecture combining a GPT-like autoregressive system with a diffusion-based audio encoder delivers both natural prosody and high audio fidelity. Higher quality reference audio produces proportionally better cloning results.
Trained on 17 languages, the model produces natural and fluent speech in each language with consistently impressive quality. Its Turkish performance is particularly noteworthy, successfully modeling Turkish-specific phonetic structures, vowel harmony, and stress patterns with accuracy. The ability to perform cross-lingual voice transfer—voicing Turkish text with an English speaker's voice, for example—is one of the defining features that makes XTTS v2 unique in the TTS landscape. This capability is invaluable for international education platforms and multilingual corporate communications. Supported languages include English, Turkish, Spanish, French, German, Italian, Portuguese, Polish, Dutch, Japanese, Korean, Chinese, and Arabic.
Released as open source, the model can run locally, preserving the privacy of voice data and eliminating cloud dependencies for sensitive applications. It provides easy integration through its Python API and Gradio interface with comprehensive documentation. Programmatic access is available through the Coqui TTS library, and model weights can be accessed on Hugging Face for flexible deployment. Streaming support enables use in real-time applications where vocalization begins instantly as text chunks arrive, keeping latency to a minimum for responsive interactions.
Achieving high naturalness scores in MOS (Mean Opinion Score) tests, XTTS v2 supports advanced features such as emotion control and speech rate adjustment for fine-tuned output. It reaches near-real-time inference speeds on GPU hardware and delivers reasonable performance on CPU as well. Docker support facilitates easy deployment to production environments with scalable architecture. The model can be converted to ONNX format for optimization across different inference engines and hardware platforms.
XTTS v2 serves a wide range of applications including voice assistants, multilingual customer service, educational platforms, audiobook production, video dubbing, and content localization across media formats. Actively supported by the developer community, the model continues to evolve with regular updates and new language additions that expand its global reach. Flexible licensing options are available for commercial projects, while the model remains completely free for research and personal use. It particularly democratizes professional voice production for independent content creators and small studios who previously lacked access to high-quality multilingual TTS technology.
Use Cases
Audiobook Production
Creating professional audiobook content by converting books to natural voice narration.
Multilingual Customer Service
Creating automated customer support systems by generating natural voice responses in 17 different languages.
Video and Podcast Dubbing
Natural voice dubbing of video and podcast content into different languages with voice cloning.
Accessibility Solutions
Converting text content to natural and intelligible audio format for visually impaired users.
Pros & Cons
Pros
- Voice cloning with 85-95% similarity accuracy using only 3-10 seconds of reference audio
- Supports 17 languages with natural-sounding multilingual speech generation
- Streaming inference with less than 200ms latency suitable for real-time applications
- Produces voice quality that rivals commercial text-to-speech alternatives
- Open-source codebase allows self-hosting and customization
Cons
- Makes pronunciation errors that single-language models like VITS avoid, especially in less common languages
- Coqui AI shut down in December 2025, leaving the project without official maintenance or support
- Licensed under Coqui Public Model License restricting commercial use without separate agreement
- Steep learning curve — users report 2-4 weeks for basic competency, 2-3 months for advanced usage
- Audio quality and prosody consistency varies across different supported languages
Technical Details
Parameters
467M
Architecture
GPT-like + HiFi-GAN
Training Data
Proprietary multilingual dataset
License
MPL-2.0
Features
- 17 languages
- Voice cloning
- Emotion control
- Streaming
- 6s cloning
- Fine-tuning support
- Open source
Benchmark Results
| Metric | Value | Compared To | Source |
|---|---|---|---|
| MOS (Mean Opinion Score) | 4.2/5.0 | YourTTS: 3.8 | Coqui TTS Official Benchmark |
| Konuşmacı Benzerliği (Speaker Similarity) | 0.68 (cosine, ECAPA-TDNN) | Bark: 0.45 | Coqui TTS Evaluation |
| Desteklenen Diller | 17 dil | Bark: 13+ dil | GitHub Repository |
| Gerçek Zamanlı Faktör (RTF) | ~0.8x (A100 GPU) | VITS: ~0.2x | Coqui TTS Docs |
Available Platforms
Frequently Asked Questions
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